Evaluating the impact of exercise on intermediate disease markers in overweight and obese individuals through a network meta-analysis of randomized controlled trials

The aim of this study is to investigate the impact of exercise on intermediate disease markers in populations with overweight and obesity, providing evidence-based recommendations for clinicians to utilize these markers in developing exercise prescriptions for this group. The study was conducted by retrieving data from PubMed, Embase, Cochrane Library, Web of Science, and CNKI and only including Randomized Controlled Trials (RCTs) to examine the effect of different exercise interventions on intermediate disease markers in overweight and obese people. The quality of the included studies was evaluated using the Cochrane Bias Risk Assessment tool and the data was analyzed using Stata 15.1 data analysis software. The RCTs were collected from January 2017 to March 2024. A total of 56 RCTs were included and the results of 10 outcomes were analyzed using random effects meta-analysis. The total sample size used in the study was 3193 The results showed that resistance training significantly reduced total cholesterol (SUCRA: 99.9%), triglycerides (SUCRA: 100.0%), low-density lipoprotein (SUCRA: 100.0%), systolic pressure (SUCRA: 92.5%), and increased high-density lipoprotein (SUCRA: 100.0%). Aerobic exercise significantly reduced insulin (SUCRA: 89.1%) and HbA1c (SUCRA: 95.3%). Concurrent training significantly reduced HOMA-IR (SUCRA: 93.8%), diastolic blood pressure (SUCRA: 71.2%) and Glucose (SUCRA: 87.6%). Exercise has a significant impact on intermediate disease markers in populations with overweight and obese. Compared with no exercise, exercise lowers total cholesterol, triglycerides, LDL, systolic blood pressure, diastolic blood pressure, HOMA-IR, insulin, and HbA1c, and increases HDL in people with overweight and obese. These findings provide evidence-based recommendations for exercise interventions aimed at weight reduction and the prevention of chronic diseases in individuals with overweight and obese.


Study selection
The screening and exclusion of literature was conducted using the EndNote literature management software.The process began with two researchers reviewing the titles of the literature to eliminate duplicates and any nonrandomized controlled trial studies, review papers, conference papers, protocols, and correspondence.Next, both researchers read the abstracts of the remaining literature to determine which studies to include and which to exclude.Finally, the full text of the remaining studies was read by both researchers to confirm their inclusion.If there were any discrepancies in the final selection of studies, the two researchers discussed and resolved the issue with the assistance of a third researcher.

Data extraction
A seven-item, standardized and pre-selected data extraction form was used to record data for inclusion in the study under the following headings: (1) author, (2) year of publication, (3) country, (4) study period, (5) sample size, (6) mean age, and (7) details of the exercise intervention.

Risk of bias evaluation of the included RCTs
According to the Cochrane Intervention Systematic Review Manual, two review authors assessed the risk of literature bias using the widely recognized Cochrane tool, considered the gold standard for assessing risk of bias in randomized controlled trials (RCTs).The assessment was based on six key components: selection bias, including the proper generation of random sequences and allocation concealment; performance bias, including participant and personnel blinding; detection bias, including outcome assessment blinding; attrition bias, which addresses incomplete outcome data; reporting bias, which examines selective reporting; and other bias, such as crossover carryover effects in RCTs 15 .The results of this assessment were clearly and concisely presented visually.We also used the STATA software to generate funnels to assess potential publication bias in small studies based on symmetry criteria.

Data analysis
In this study, we conducted a meta-analysis to investigate the effects of various exercise interventions on disease markers among overweight and obese people.To maintain consistency in the studies, all interventions were Vol:.(1234567890)

Scientific Reports |
(2024) 14:12137 | https://doi.org/10.1038/s41598-024-62677-wwww.nature.com/scientificreports/quantified as continuous variables.We used a random-effects model to accommodate any differences between studies.Subsequent analysis was carried out using the STATA 15.1 software.Here, we used standardized mean differences (SMDs) to measure different effect sizes between different interventions.In addition, 95% confidence intervals were used to estimate the possible range of these differences.We plan to employ the nodal method as a means of quantifying and demonstrating the concordance between indirect and direct comparisons.These calculations will be conducted using the Stata software.If the P-value is greater than 0.05, it would indicate a successful consistency test 16 .To visualize the relationships between different motor interventions, a network diagram was utilized.This diagram, generated using Stata software, depicted each mode of intervention as a node, with the connecting lines between nodes representing direct comparisons.The size of each node reflected the volume of literature related to the corresponding exercise intervention, and the thickness of connecting lines represented the number of studies comparing the interventions 17 .
The Cumulative Ranking Curve (SUCRA) method was used to rank the relative effectiveness of each intervention.This method converts the therapeutic effect of each intervention into an area chart, where the values of the area and area under the curve represent the likelihood of the optimal intervention.In this study, the larger the area under the curve and the closer the value was to 100%, the better the effect of the intervention.In this study, the larger the area under the curve, the closer the value was to 100%, the better the effect of the intervention.

Study and identification and selection
A total of 7218 documents were retrieved from the electronic database, and an additional 22 documents were manually searched.After eliminating duplicates, the remaining 5623 documents were read for titles and abstracts, and 5281 articles were excluded due to irrelevance after reviewing their titles and abstracts.The remaining 342 documents were read in full and 286 documents were again excluded (for reasons including: non-randomized controlled trials, incomplete data, conference papers and failure to meet the interventions included in this review), leaving a final remaining 56 documents to be included in this study (Fig. 1).

Quality assessment of the included studies
Forty-seven subjects were classified as medium risk, and nine as high risk.We found that no study achieved complete blinding of both subjects and measurers.Specific details will be presented in Fig. 2.
Forty-seven studies reported TC as an outcome indicator,49 studies reported TG as an outcome indicator, 48 studies reported HDL as an outcome indicator, 48 studies reported LDL as an outcome indicator, 37 studies reported SBP as an outcome indicator, 35 studies reported DBP as an outcome indicator, 34 studies reported Glu as an outcome indicator, 20 studies reported insulin as an outcome indicator, 23 studies reported HOMA-IR as an outcome indicator and 11 studies reported Hba1c as an outcome indicator.
There were six studies from USA, six studies from Brazil, one study from South Africa, seven studies from Iran, seven studies from China, four studies from the Spain, one study from Saudi Arabia, one study from Ghana, one study from The Republic of Azerbaijan, one study from Serbia, two studies from Denmark, one study from Tunisia, one study from Beaumont, two studies from Norway, one study from Chile, one study from Switzerland, one study from Germany, two studies from Australia, one study from Portugal, one study from Saudi Arabia, one study from Greece, two studies from Malaysia, one study from Egypt, one study from Sweden, one study from Korea, one study from Turkey, one study from Estonia, one study from Ireland.The characteristics of the included studies are shown in Table 2.

Total cholesterol (TC)
All direct and indirect comparisons between all studies were evaluated for consistency and inconsistency, with all P-values exceeding 0.05.This suggests an acceptable level of agreement among the studies.More details will be provided in Fig. 3B.
The results of the Network meta-analysis showed that relative to the control group's routine measures, resistance training [MD = − 30.29, 95% CI (− 50.17, − 10.40)], concurrent training [MD = 30.29,95% CI (10.40, 50.17)], aerobic exercise [MD = 33.69,95% CI (14.23, 53.15)]were superior to the control group in reducing TC value, the details will be shown in Table 3.The probability ranking of the different exercise interventions in terms of reducing TC value was ranked first by resistance training in the SUCRA for (SUCRA: 99.9% as shown in Fig. 3C).(16.63, 31.30)]weresuperior to the control group in reducing TG value, the details will be shown in Table 4.The probability ranking of the different exercise interventions in terms of reducing TG value was ranked first by resistance training in the SUCRA for (SUCRA: 100% as shown in Fig. 4C).

High density lipoprotein (HDL)
All P-values for indirect and direct comparisons between all studies were tested for consistency and inconsistency, and all P-values were greater than 0.05, indicating that the effect of consistency between studies was acceptable.Details will be shown in Fig. 5B.
The results of the Network meta-analysis showed that relative to the control group's routine measures,  Low density lipoprotein (LDL) Every P-value from indirect and direct comparisons across all studies was scrutinized for both consistency and inconsistency.All P-values turned out to be more than 0.05, pointing to a commendable level of coherence among the studies.More comprehensive details will be presented in Fig. 6B.The results of the Network meta-analysis showed that relative to the control group's routine measures, resistance training [MD = − 32.95, 95% CI (− 52.06, − 13.86)], aerobic exercise [MD = 29.67,95% CI (16.22,43.13)], concurrent training [MD = 32.95,95% CI (13.86, 52.06)], were superior to the control group in reducing LDL value, the details will be shown in Table 6.The probability ranking of the different exercise interventions in terms of reducing LDL value was ranked first by resistance training in the SUCRA for (SUCRA: 100% as shown in Fig. 6C).

Systolic pressure (SBP)
All P-values stemming from both indirect and direct comparisons among every study were assessed for uniformity and disparity.All of these P-values exceeded the 0.05 threshold, signaling an acceptable level of consistency among the studies.Further elaborations will be depicted in Fig. 7B.
The results of the Network meta-analysis showed that relative to the control group's routine measures, resistance training [MD = − 4.47, 95% CI (− 11.84, 2.90)], concurrent training [MD = 4.19, 95% CI (− 2.78, 11.16)], aerobic exercise [MD = 4.76, 95% CI (− 2.21, 11.73)] were superior to the control group in reducing SBP value, the details will be shown in Table 7.The probability ranking of the different exercise interventions in terms of reducing SBP value was ranked first by resistance training in the SUCRA for (SUCRA: 92.5% as shown in Fig. 7C).

Diastolic pressure (DBP)
All P-values for indirect and direct comparisons between all studies were tested for consistency and inconsistency, and all P-values were greater than 0.05, indicating that the effect of consistency between studies was acceptable.Details will be shown in Fig. 8B.8C).

Glucose (Glu)
P-values associated with indirect and direct comparisons across all studies were examined for their consistency and inconsistency.Each of these P-values surpassed 0.05, which underscores an acceptable degree of harmony among the various studies.Additional particulars will be illustrated in Fig. 9B The results of the Network meta-analysis showed that relative to the control group's routine measures, concurrent training [MD = − 0.47, 95% CI (− 1.00, 0.05)], aerobic exercise [MD = − 0.40, 95% CI (− 0.89, 0.09)], were superior to the control group in reducing Glu value, the details will be shown in Table 9.The probability ranking of the different exercise interventions in terms of reducing Glu value was ranked first by concurrent training in the SUCRA for (SUCRA: 87.6% as shown in Fig. 9C).

Insulin
Every P-value from both direct and indirect comparisons across all studies was subjected to tests for consistency and inconsistency.All of these P-values registered above 0.05, signifying an acceptable degree of uniformity across the studies.More extensive details will be portrayed in Fig. 10B.www.nature.com/scientificreports/value, the details will be shown in Table 11.The probability ranking of the different exercise interventions in terms of reducing HOMA-IR value was ranked first by concurrent training in the SUCRA for (SUCRA:93.8% as shown in Fig. 11C).

Hemoglobin A1c (Hba1c)
Each P-value from indirect and direct comparisons involving all studies was evaluated for uniformity and variance.Every P-value was found to be above 0.05, which suggests a satisfactory level of agreement within the studies.More specifics will be outlined in Fig. 12B.The results of the Network meta-analysis showed that relative to the control group's routine measures, aerobic exercise [MD = − 0.10 (− 0.19, − 0.00), 95% CI (− 0.19,0.00)]were superior to the control group in reducing Hba1c value, the details will be shown in Table 12.The probability ranking of the different exercise interventions in terms of reducing Hba1c value was ranked first by aerobic exercise in the SUCRA for (SUCRA:95.3% as shown in Fig. 12C).

Publication bias test
We constructed separate funnel plots for all outcome indicators to test for possible publication bias.After visually examining the funnel plot did not reveal any significant publication bias 55 .Details as shown in Fig. 13.

Discussion
In this study, we investigated the effects of various exercise interventions on the levels of abnormal intermediate disease biomarkers in populations with overweight and obese.A total of 56 studies, including 14 different exercise programs and 3193 people with obese and overweight, were included in the analysis, resulting in a substantial sample size.Our research findings suggest that resistance training can significantly improve dyslipidemia, reduce   [56][57][58][59] .The intermediate disease biomarkers discussed in this article reflect people' blood lipid, blood glucose, blood pressure levels.These markers are closely related to the metabolic and cardiovascular status of people, as well as the development of chronic diseases.Therefore, by analyzing these intermediate disease biomarkers, healthcare providers can improve people' overall health status and reduce the risk of chronic diseases based on the exercise intervention recommendations provided herein.

Aerobic exercise
Aerobic exercise is widely regarded as the most effective method for weight loss in obese individuals ,this form of exercise, which involves continuous physical activity leading to increased heart rate and respiration, not only enhances strength and endurance but also stimulates metabolism, reduces fat storage, and promotes cardiovascular health, thereby contributing to overall well-being 60,61 .
The outcomes of our network meta-analysis revealed that compared to no exercise, aerobic exercise significantly managed blood lipid levels, blood pressure, and blood glucose in overweight and obese individuals.Moreover, among various exercise modalities, aerobic exercise stood out as the most effective method in lowering insulin and glycated hemoglobin concentrations within this population.
Clinicians can tailor aerobic exercise prescriptions to people with overweight and obese based on the results of this study [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34] , and can choose appropriate forms of exercise from dance, walking, endurance training, cycling, running, and MICT.It is recommended that the duration of each exercise range from 30 to 90 mins, with a frequency of three to six times a week.Exercise intensity should be tailored to the patient's specific needs in order to effectively lower their blood glucose levels.Regular aerobic exercise can improve metabolic and physiological functions, alleviate physical strain, and boost overall health status.

Resistance training
Our research findings reveal that all exercise types can effectively lower people' abnormal blood lipid levels when compared to sedentary control groups.Nevertheless, resistance training stands out as the most successful exercise type within this study.Resistance training not only has the ability to regulate blood lipid levels but can also decrease people' systolic blood pressure.It is crucial to highlight that, when compared to the non-exercising

Strengths and limitations
Our study encompasses 56 research projects and 3193 people, which constitutes a substantial sample size, and offers a comprehensive and updated review of exercise interventions in people with overweight and obese.We've integrated three innovative interventions-water sports, whole-body vibration training, and rope training-to compare with other interventions, thereby delivering the most recent and exhaustive evidencebased recommendations.
However, our study shares some limitations with the research it is based on.Despite our efforts to control study heterogeneity, some heterogeneity is inevitable between studies, such as the proportion of male and female participants and regional variations.Readers should interpret our findings cautiously due to the strict literature screening criteria, the limited number of included studies, and limited direct comparison evidence for certain interventions.This highlights the need for further expansion of relevant research.
Lastly, our study only included 14 exercise interventions that met the literature screening criteria, but in reality, there are many more interventions that can positively impact the intermediate markers of individuals with overweight and obese.Future research can broaden the scope by including more types of exercise interventions, offering more choices for different people; analyze the response differences among different populations (such as age, gender, race, and cultural background) to exercise interventions, to develop more personalized exercise plans; and explore the long-term effects of exercise interventions to better assess their sustainability in improving the health of overweight and obese people.
In summary, although our study has some limitations, it still provides valuable information on exercise interventions for overweight and obese people.By analyzing various types of exercise interventions, we offer evidence-based recommendations for healthcare providers on how to develop more effective treatment strategies.In the future, we hope to see more research on exercise interventions to better meet the needs of different people and help them achieve healthier lifestyles.

Conclusions
The study hints at potential mechanisms by which resistance, aerobic, and concurrent training could influence improvements in health markers for individuals with overweight and obesity, thus shedding light on the varying impacts of different exercise modalities on health outcomes.Resistance training enhances lean muscle mass, leading to an increase in metabolic rate and fat oxidation, improvement in lipid profiles , and reduction in systolic blood pressure.Conversely, aerobic training primarily improves insulin sensitivity and cardiovascular health while lowering blood glucose levels but may not significantly enhance muscle strength.Concurrent training combines the advantages of both exercise types by addressing diastolic blood pressure and blood glucose levels despite potential interference effects that could impact optimal strength or endurance gains.
Each modality offers distinct advantages: resistance training is optimal for enhancing muscle strength and lipid profiles, aerobic training excels in providing cardiovascular benefits and managing glucose levels, while concurrent training provides a comprehensive approach to simultaneously address multiple health markers.However, the selection of exercise should be tailored to individual health objectives, preferences, and specific conditions while acknowledging the limitations and strengths associated with each modality (Supplementary Information).
Based on the collective insights derived from this study, it is recommended that clinicians adopt a personalized exercise prescription approach when working with overweight and obese populations.By aligning exercise modalities with individual health profiles and objectives, clinicians can develop targeted interventions that not only enhance overall health but also mitigate the risk of chronic conditions.This approach capitalizes on the distinct advantages offered by resistance, aerobic, and concurrent training to cater to diverse health needs.

Figure 1 .
Figure 1.Flow diagram of literature selection.

Figure 2 .
Figure 2. Risk of bias summary & risk of bias graph.

Table 2 .
Characteristics of the studies included in the meta-analysis.CON A control group that normally conducts daily life (no exercise), T experimental group, C control group, TC total cholesterol, TG triglyceride, HDL high-density lipoprotein, LDL low density lipoprotein-Cholesterol, SBP systolic pressure, DBP diastolic blood pressure, Glu glucose, HOMA-IR homeostatic model assessment for insulin resistance, HbA1c hemoglobin A1c, RT resistance training, CT concurrent training, HIIT high-intensity interval training, MIIT Moderate-intensity interval training, MICT moderate-intensity continuous training, T + C The ages of the experimental and control groups were not reported separately in the study, only the overall age was reported, NA unavailable, Freq frequency.

Table 3 .
League table on TC.

Table 4 .
League table on TG.

Table 5 .
League table on HDL.

Table 6 .
League table on LDL.systolic blood pressure, while concurrent training can significantly reduce diastolic blood pressure and blood glucose levels.Aerobic exercise can significantly reduce blood glucose levels in obese and overweight individuals.Aerobic exercise is considered the most effective exercise intervention for reducing glycated hemoglobin and insulin levels, resistance training is the most effective exercise intervention for lowering systolic blood pressure and blood lipids, and concurrent training is the most effective exercise intervention for regulating diastolic blood pressure, reducing blood glucose and insulin resistance.Numerous previous studies have shown that intermediate disease biomarker levels are abnormal in populations with overweight and obese

Table 7 .
League table on SBP.

Table 8 .
League table on DBP.

Table 9 .
League table on Glu.In summary, our study bears clinical significance in two key respects: firstly, it provides a theoretical foundation for the fact that exercise can significantly mitigate abnormal intermediate disease markers in people with overweight and obese; secondly, it allows clinicians to integrate our findings with people' abnormal intermediate disease markers to tailor exercise prescriptions, thereby fostering overall patient health.